1. Field of the Invention
Embodiments of the invention provide a method and apparatus for recognition and tagging of multiple layered entropy coding system.
2. Description of the Related Art
The point of wired and wireless communication technology and its applications are centered on “access anywhere” concept. This includes the access to data, software and services. The interface must be standard and requires software and hardware integration. Communication technology is a leading edge technology driver that involved multi-layered sophisticated technology and algorithms, from several decades of research and applications. In general, communication technologies include multiple layered source coding, channel coding, network resource access, which are all involved with both server hardware and software as well as integration technologies. Most of them are very computational intensive and involved transformation and entropy coding technologies, as illustrated in FIG. 1. More specifically, intermediate components between an audio video source and RF transmission comprise quantization 100, compression 110, cipher coding channel coding 120, domain transformation 130, source coding 140, and interleaving spreading 150. Multiplexing (MUX) 160, error correction 170, and modulation 180 are also included.
The source-coding portion 140 included voice processing, relational database access, audio and video compression, voice recognition, and particularly, VLC (Variable Length Coding) coding to gain better channel efficiency. The focus point is on the standard conforming, interoperability, and end-to-end solution. Thus combined rich history of unevenly advances of varies aspect of communication technologies, as well as un-matching growth rate of channel capacity, together have generated many different coding and modulation schemes. Those schemes that being applied to the source contents have many effects on channel capacity and the content's entropy itself.
As part of nature, the original sources contents tend to have bigger entropy value with time passed by, originated from second law of thermo dynamics. Entropy change, ΔS, measures how much information energy is spread out in a channel, or how spread out is the energy of a system (either always involving temperature T or source contents): ΔS=q/T. So, in that equation, q (the enthalpy of fusion) is how much energy was spread out in the channels. In terms of information theory, the entropy of an information source S is defined as:
      H    ⁡          (      S      )        =      η    =                  ∑        i            ⁢                          ⁢                        p          i                ⁢                  log          2                ⁢                  1                      p            i                              
Where pi is the probability that symbol Si in S will occur.
The original source contents tents to have very uneven entropy distribution, as shown in FIG. 2. Specifically, graphs 200 and 210 illustrate percentage distribution (x-axis) versus probability (y-axis). Graph 200 illustrates that without differential coding, the entropy is 6.42 bits; and, graph 210 illustrates that with differential coding, the entropy is 6.07 bits. As the statistics done to source contents can show, the frequency distribution of digits in a series, for example, can be shown to have an important influence on the randomness of the series. Just a simple inspection suggests that a series consisting entirely of either 0's or 1's is far from random, and the algorithmic approach confirms that conclusion. If such a series is n digits long, its complexity is approximately equal to the logarithm to the base 2 of n. The series can be produced by a simple algorithm such as “Print 0 n times,” in which virtually all the information needed is contained in the binary numeral for n. The size of this number is about log 2 n bits. Since for even a moderately long series the logarithm of n is much smaller than n itself, such numbers are normally low complexity.
There are many nested coding algorithms added to the original source contents, both in the source coding process and channel coding process. The entropy of the contents was averaged out already during the source coding process, additional channel coding seems did not change the entropy of the source contents much. But added bit for error protection and multiple access purposes.
The problem come from multiple layered algorithms tend to repeated coding the source contents after the initially VLC coding, thus greatly reduce the intended effect of entropy coding but cause adverse effect of adding unnecessary bit to the originally entropy coded contents.